One or more frames of video data may depict content that is determined to likely be of interest to a user. A video segment that includes the one or more frames may be determined. Based at least partly on one or more first summarization parameters associated with the user, a first video summarization may be generated, where the first video summarization includes the first video segment and possibly other video segments associated with the video data. The first video summarization may be provided to the user. Upon receiving data that is representative of user feedback relating to the first video summarization, one or more second summarization parameters may be determined based at least partly on the data. A second video summarization of the video data may be generated based at least partly on the one or more second summarization parameters. The second video summarization may then be provided to the user.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system comprising: memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: receiving video data generated by a camera of a user device; determining first summarization parameters based on data associated with a user account, the data including at least one of a search history of items searched for via a website, a browse history of items viewed via the website, or a purchase history of items purchased via the website; generating a first video summarization of the video data based on the first summarization parameters, wherein generating the first video summarization comprises: generating a first video segment that includes a first frame of the video data and that is of a first duration that is less than a total duration of the video data; generating a second video segment that includes a second frame of the video data that is of a second duration that is less than the total duration of the video data; and generating at least one of the first video segment or the second video segment based on a first directorial style associated with the first summarization parameters; receiving, from the user device, a request to modify the first video summarization; determining, based on the request, second summarization parameters that are different than the first summarization parameters, wherein the second summarization parameters are based at least partly on: identifying one or more prior video summarizations previously generated in association with the user account; and determining a second directorial style different than the first directorial style and associated with the one or more prior video summarizations; generating a second video summarization of the video data based on the second summarization parameters, the second video summarization being different than the first video summarization; and sending the second video summarization to the user device.
The system automates video summarization by analyzing user behavior to personalize video editing. It addresses the challenge of manually editing long videos by generating concise summaries tailored to individual preferences. The system receives video data from a user device and determines summarization parameters based on the user's online activity, such as search, browse, or purchase history from a website. Using these parameters, it creates a first video summary by extracting key frames and segments, applying a specific directorial style (e.g., pacing, transitions, or emphasis) derived from the user's data. If the user requests modifications, the system adjusts the summarization by analyzing prior summaries associated with the user account to identify a new directorial style. It then generates a revised summary with different segments and styling, ensuring the output aligns with the user's evolving preferences. The system dynamically adapts to user feedback, improving personalization over time. This approach streamlines video editing by leveraging behavioral data to automate and refine summarization.
2. The system as recited in claim 1 , wherein the operations further comprise determining the first frame of the video data and the second frame of the video data by: determining a curve that includes multiple data points that comprise a first data point that is representative of a first interest value assigned to the first frame and a second data point that is representative of a second interest value assigned to the second frame; determining that the first data point constitutes a first local maxima of the curve; determining that the second data point constitutes a second local maxima of the curve; selecting the first frame based on the first data point constituting the first local maxima of the curve; and selecting the second frame based on the second data point constituting the second local maxima of the curve.
The invention relates to video processing systems that analyze video data to identify key frames for summarization or other applications. The problem addressed is the need to automatically select frames that are most representative or interesting within a video sequence, often for purposes such as video summarization, content analysis, or user engagement optimization. The system processes video data by determining interest values for individual frames, which quantify how significant or engaging each frame is. These interest values are plotted as data points on a curve, where each point corresponds to a frame's interest value. The system then analyzes this curve to identify local maxima—points where the interest value is higher than adjacent frames. The first and second frames are selected based on these local maxima, ensuring they represent peaks in the video's interest or significance. This approach helps automate the selection of key frames without manual intervention, improving efficiency and consistency in video analysis applications. The method ensures that the chosen frames are not only relevant but also distinct from one another, enhancing the quality of video summaries or other derived outputs.
3. The system as recited in claim 1 , wherein the operations further comprise: determining that a third frame of the video data depicts a first scene; generating a third video segment that includes the third frame and that is of a third duration that is less than the total duration of the video data; determining that a fourth frame of the video data depicts a second scene; generating a fourth video segment that includes the fourth frame and is of a fourth duration that is less than the total duration of the video data; determining, based on a first interest value assigned to the third frame and a second interest value assigned to the fourth frame, that the third video segment is assigned a higher ranking than the fourth video segment; and determining, based on the second summarization parameters, that the third video segment is to be included in the second video summarization.
This invention relates to video summarization, specifically a system that automatically generates concise video summaries by analyzing and ranking video segments based on their content and relevance. The system processes video data to identify key frames depicting distinct scenes, then generates shorter video segments centered around these frames. Each segment is assigned a duration shorter than the full video length. The system evaluates the importance of each segment using interest values, which may be derived from factors like visual saliency, motion, or user preferences. Segments are ranked accordingly, and the highest-ranking segments are selected for inclusion in the final summary based on predefined summarization parameters, such as desired summary length or scene diversity. The system ensures the summary captures the most significant moments while maintaining brevity. This approach is useful for applications like video editing, surveillance, or content recommendation, where concise, relevant summaries are needed. The invention improves upon traditional summarization methods by dynamically adjusting segment selection based on computed interest values and configurable parameters.
4. The system as recited claim 1 , wherein the operations further comprise: determining that a third frame of the video data depicts a first scene; generating a third video segment that includes the second frame and is of a third duration that is less than the total duration of the video data; determining that a similarity between the second video segment and the third video segment is above a threshold value; and determining, based on the second summarization parameters, that the third video segment is to be included in the second video summarization.
This invention relates to video summarization, specifically a system that automatically generates concise video summaries by analyzing and selecting key frames or segments. The problem addressed is the need to efficiently condense long video content while preserving important scenes and maintaining coherence in the summary. The system processes video data by identifying frames or segments that represent distinct scenes. It generates multiple video segments of varying durations, each capturing different portions of the original video. The system compares these segments to assess their similarity, using a threshold value to determine whether they depict overlapping or redundant content. Based on predefined summarization parameters, the system selects segments for inclusion in the final summary, ensuring diversity and relevance. The parameters may include factors like scene importance, duration constraints, or user preferences. The invention ensures that the summary avoids redundancy by excluding segments that are too similar to already selected ones. This approach optimizes the summarization process, making it suitable for applications like surveillance, social media, or content archiving where concise yet informative summaries are needed. The system dynamically adjusts segment selection based on the similarity analysis, ensuring the summary remains coherent and representative of the original video.
5. The system as recited in claim 1 , wherein the operations further comprise: determining that the purchase history indicates that an item of the items was purchased in association with the user account; and generating the first video summarization in a particular directorial style that is associated with a category of items that includes the item.
The invention relates to personalized video summarization systems that generate customized video content based on user purchase history. The problem addressed is the lack of personalized and contextually relevant video content for users, particularly in e-commerce or media platforms where user preferences are not fully leveraged. The system analyzes a user's purchase history to identify items associated with their account. When generating a video summarization, the system selects a directorial style tailored to the category of the purchased item. For example, if a user frequently buys fitness equipment, the video summarization may adopt a dynamic, high-energy editing style. Similarly, if the user purchases luxury goods, the video may use a sophisticated, cinematic style. This approach ensures the video content aligns with the user's interests and enhances engagement. The system integrates with a broader framework that processes input data, such as user interactions or preferences, to generate video summaries. The summarization process involves selecting relevant segments, applying stylistic edits, and assembling them into a cohesive video. By dynamically adjusting the directorial style based on purchase history, the system provides a more personalized and immersive experience. This method improves user satisfaction and retention by delivering content that resonates with individual preferences.
6. A method comprising: determining multiple video segments associated with video data, wherein determining the multiple video segments associated with the video data comprises determining a first video segment of the multiple video segments that is associated with at least one frame of the video data and that has a duration that is less than a total duration of the video data; determining one or more summarization parameters based at least partly on a user account and prior to generating a video summarization of the video data, wherein determining the one or more summarization parameters includes: identifying one or more prior video summarizations previously generated in association with the user account; and determining one or more characteristics of a directorial style associated with the user account; and generating, based at least partly on the one or more summarization parameters, the video summarization.
This invention relates to automated video summarization, addressing the challenge of efficiently condensing video content while adapting to user preferences. The method involves analyzing video data to identify multiple video segments, including at least one segment with a duration shorter than the full video. These segments are selected based on their relevance to key frames or other criteria. Before generating the summary, the system determines summarization parameters tailored to a specific user account. This includes analyzing prior video summaries created for the user to identify patterns in their preferences, such as favored segment lengths, pacing, or content types. Additionally, the system assesses the user's directorial style, which may reflect their preferred editing techniques, such as transitions, pacing, or emphasis on certain visual elements. Using these parameters, the system generates a personalized video summary that aligns with the user's historical behavior and stylistic preferences. The approach ensures that the summarization process is adaptive, leveraging user-specific data to produce more relevant and engaging condensed versions of video content.
7. The method as recited in claim 6 , further comprising: assigning an interest value to a frame of the video data based at least partly on at least one of a person or a scene depicted in the frame; determining that the interest value is above a threshold value; determining a video segment of the multiple video segments, wherein determining the video segment comprises determining that the video segment includes the frame; and selecting the video segment to be included in the video summarization.
This invention relates to video summarization, specifically a method for automatically selecting key video segments based on interest values assigned to frames. The problem addressed is the need for efficient and meaningful video summarization, particularly in scenarios where large volumes of video data must be condensed into shorter, relevant summaries. The method involves analyzing video data divided into multiple segments. Each frame within the video is evaluated to assign an interest value, which is determined based on factors such as the presence of a person or a specific scene depicted in the frame. If the interest value exceeds a predefined threshold, the frame is identified as significant. The method then identifies the video segment containing this high-interest frame and selects that segment for inclusion in the final video summary. This ensures that only the most relevant portions of the video are retained, improving the efficiency and relevance of the summarization process. The approach leverages content-based analysis to prioritize frames and segments that are likely to be of greater interest to viewers, enhancing the utility of automated video summarization systems.
8. The method as recited in claim 6 , further comprising: determining that the first video segment includes a first frame of the video data that depicts first content; determining a second video segment of the multiple video segments, wherein determining the second video segment comprises determining that the second video segment includes a second frame of the video data that depicts second content; assigning a first rank to the first video segment based at least partly on the first content; assigning a second rank to the second video segment based at least partly on the second content; determining that the first rank is greater than the second rank; and selecting the first video segment to be included in the video summarization.
Video summarization systems analyze video data to generate concise summaries by identifying and selecting key segments. A challenge in this domain is efficiently ranking and selecting video segments based on their content to produce a meaningful summary. The invention addresses this by determining multiple video segments within a video and analyzing their content. For each segment, the system identifies frames depicting specific content and assigns a rank based on that content. For example, a first video segment containing a frame with first content is ranked higher than a second segment with different content. The system compares the ranks and selects the higher-ranked segment for inclusion in the summary. This ensures that the most relevant or important segments, as determined by their content, are prioritized in the final output. The method improves summarization accuracy by dynamically evaluating and ranking segments based on their depicted content, enhancing the quality of generated video summaries.
9. The method as recited in claim 6 , further comprising determining that the video summarization includes at least the first video segment and a second video segment of the multiple video segments, wherein determining that the video summarization includes the at least the first video segment and the second video segment comprises determining that the first video segment includes one or more first frames of the video data that depicts first content and that the second video segment includes one or more second frames of the video data that depict second content.
This invention relates to video summarization, specifically a method for analyzing and selecting video segments to create a concise summary. The problem addressed is the need to automatically identify and include relevant portions of a video while excluding less important content, ensuring the summary retains key information. The method involves processing video data to identify multiple video segments, each containing frames depicting specific content. A video summarization is generated by determining which segments to include based on their content. The summarization includes at least a first video segment and a second video segment, where the first segment contains frames depicting first content and the second segment contains frames depicting second content. The selection process ensures that the summary captures diverse or critical portions of the original video, improving efficiency and relevance. The method may also involve analyzing the video data to detect transitions, objects, or events within the frames to assess their importance. Segments are selected based on criteria such as visual distinctiveness, temporal relevance, or user-defined preferences. The summarization can be adjusted dynamically to prioritize certain types of content or exclude redundant segments, enhancing the overall quality of the summary. This approach is useful for applications like surveillance, social media, or automated content curation.
10. The method as recited in claim 6 , further comprising: determining that the first video segment includes a first frame of the video data that depicts first content; determining a second video segment of the multiple video segments, wherein determining the second video segment comprises determining that the second video segment includes a second frame of the video data that depicts second content; determining that a similarity between the first content and the second content is greater than a threshold value; associating the first video segment and the second video segment with a category; ranking the first video segment, the second video segment, and additional video segments of the multiple video segments within the category; determining that a first ranking assigned to the first video segment is greater than a second ranking assigned to the second video segment; and selecting the first video segment to be included in the video summarization.
This invention relates to video summarization, specifically a method for identifying and selecting key video segments to create a concise summary. The problem addressed is the efficient and accurate extraction of relevant content from long videos, ensuring that the summary retains meaningful information while reducing redundancy. The method processes video data divided into multiple segments. It identifies a first video segment containing a frame depicting specific content and a second video segment with a frame depicting different content. The system compares the content of these segments, determining if their similarity exceeds a predefined threshold. If so, both segments are categorized together. Within this category, the segments and additional related segments are ranked based on relevance or importance. The highest-ranked segment is selected for inclusion in the final video summary, ensuring the most significant content is prioritized. This approach improves video summarization by reducing redundancy and enhancing the coherence of the summary, making it more useful for applications like content analysis, surveillance, or user-generated content platforms. The method dynamically categorizes and ranks segments, ensuring the summary is both concise and representative of the original video.
11. The method as recited in claim 10 , further comprising: receiving, from a user device associated with the user account, data representative of a request to at least one of modify or replace the first video segment; selecting the second video segment to be included in a second video summarization of the video data; and sending, to the user device, the second video summarization.
This invention relates to video summarization systems that allow users to modify or replace segments within an automatically generated video summary. The technology addresses the problem of static video summaries that do not adapt to user preferences or evolving content needs. The system generates an initial video summary by analyzing video data to identify key segments, such as highlights or important scenes, and compiling them into a condensed version. Users can then request modifications, such as replacing or adjusting segments within the summary. The system processes these requests by selecting alternative segments from the original video data or other sources to create an updated summary. The revised summary is then sent back to the user device, ensuring the output remains relevant and personalized. This approach enhances user control over automated video summarization, allowing for dynamic adjustments based on feedback or changing requirements. The invention improves upon prior systems by enabling iterative refinement of video summaries without requiring manual editing of the entire video.
12. The method as recited in claim 6 , further comprising; receiving, from a user device associated with the user account, data representative of a request to at least one of modify or replace the video summarization, the video summarization including at least a first video segment of the multiple video segments; determining one or more second summarization parameters, including a second directorial style that is different than the directorial style, based at least partly on the data; generating, based at least partly on the one or more second summarization parameters, a second video segment of the multiple video segments to be included in a second video summarization of the video data; and sending, to the user device, the second video summarization.
This invention relates to video summarization systems that automatically generate condensed versions of video content based on user preferences and directorial styles. The problem addressed is the lack of flexibility in existing video summarization tools, which often produce static summaries without allowing users to modify or replace segments dynamically. The system receives video data and processes it into multiple video segments. A first video summarization is generated by selecting segments based on initial summarization parameters, including a directorial style that influences pacing, transitions, and emphasis. The summarization is sent to a user device associated with a user account. The user can request modifications or replacements to the summarization. The system receives this request and determines new summarization parameters, including a different directorial style, based on the user's input. Using these parameters, a second video segment is generated and incorporated into a revised summarization. The updated summary is then sent back to the user device, allowing iterative refinement of the output. This approach enables personalized, adaptable video summaries that can be adjusted in real time.
13. The method as recited in claim 6 , further comprising determining that the one or more summarization parameters are based at least partly on at least one of input received from a user associated with the user account, default parameters, prior behavior exhibited by the user, information associated with the user account, or prior behavior exhibited by other users.
This invention relates to automated text summarization systems that generate summaries of digital content based on user-specific parameters. The problem addressed is the lack of personalized summarization in existing systems, which often produce generic summaries that do not align with individual user preferences or needs. The method involves generating a summary of digital content by analyzing the content and applying one or more summarization parameters. These parameters are dynamically determined based on various factors, including explicit input from the user, default settings, the user's past behavior, account-related information, or aggregated behavior patterns of other users. For example, if a user frequently requests concise summaries, the system may prioritize brevity in future summaries. Similarly, if a user consistently interacts with summaries containing specific keywords, the system may adjust the summarization parameters to emphasize those terms. The system may also track user interactions with summaries, such as feedback or engagement metrics, to refine the parameters over time. This ensures that the summaries evolve to better match the user's preferences. The approach improves the relevance and usefulness of automated summaries by tailoring them to individual users or groups of users with similar behaviors.
14. The method as recited in claim 6 , further comprising receiving, from a user device associated with the user account, data representative of feedback relating to the video summarization, wherein the receiving the data includes at least one of: receiving an indication of approval or disapproval of an entirety of the video summarization; receiving an indication of approval or disapproval of one or more video segments included in the video summarization; receiving a request to modify, remove, or replace one or more video segments included in the video summarization; or receiving a request to add one or more video segments of the multiple video segments to the video summarization.
This invention relates to video summarization systems that generate condensed versions of videos based on user preferences and feedback. The technology addresses the challenge of creating personalized video summaries that accurately reflect a user's interests by incorporating real-time feedback to refine the summarization process. The method involves generating a video summarization from multiple video segments, where the summarization is tailored to a user account. The system then receives feedback from a user device associated with the user account, which can include various forms of input. The feedback may indicate approval or disapproval of the entire video summarization or specific segments within it. Additionally, the user can request modifications, such as removing, replacing, or adding segments to the summarization. This feedback loop allows the system to dynamically adjust the video summary to better align with the user's preferences, improving the relevance and accuracy of the condensed content. The method ensures that the video summarization process is interactive and adaptable, enhancing user satisfaction with the generated summaries.
15. A system comprising: memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: determining that a first frame of video data depicts first content, wherein determining that the first frame of the video data depicts the first content comprises determining that the first content includes at least one of a person, an object, or a scene; determining one or more first summarization parameters based at least partly on one or more prior video summarizations previously generated in association with a user account, the one or more first summarization parameters including a first directorial style; generating a first video segment that includes the first frame and is of a first duration that is less than a total duration of the video data; generating a first video summarization of the video data that includes the first video segment based at least partly on the one or more first summarization parameters, the one or more first summarization parameters including a first directorial style; and sending, to a user device, the first video summarization.
The system automates the creation of personalized video summaries by analyzing video content and generating concise, stylized highlights. The technology addresses the challenge of efficiently summarizing long videos while tailoring the output to user preferences. The system processes video data by identifying key frames depicting people, objects, or scenes. It then determines summarization parameters, including a directorial style, based on prior video summaries associated with a user account. Using these parameters, the system generates a video segment of reduced duration from the original video. The segment is incorporated into a final video summary, which is then transmitted to a user device. The system leverages machine learning to adapt the summarization process to individual user preferences, ensuring the output aligns with their past interactions and stylistic choices. This approach enhances user engagement by delivering personalized, visually coherent video summaries that highlight relevant content while maintaining a consistent aesthetic.
16. The system as recited in claim 15 , wherein the operations further comprise: receiving, from the user device, data representative of a request to modify the first video summarization; generating, based at least partly on the data, one or more second summarization parameters that are different than the first summarization parameters, the one or more second summarization parameters including a second directorial style that is different than the first directorial style; determining that a second frame of the video data depicts second content; generating a second video segment that includes the second frame and is of a second duration that is less than the total duration of the video data; selecting, based at least partly on the one or more second summarization parameters, the second video segment; and generating, based at least partly on the one or more second summarization parameters and the second video segment, a second video summarization.
Video summarization systems automatically condense long videos into shorter, highlight-focused versions. A key challenge is adapting summaries to different user preferences while maintaining coherence and relevance. This invention improves upon prior systems by enabling dynamic modification of video summaries based on user feedback or changing preferences. The system receives a request to adjust an existing summary, then generates new summarization parameters, including a different directorial style (e.g., pacing, transitions, or emphasis). It analyzes the video to identify frames depicting relevant content, creates a new segment of appropriate length, and selects it based on the updated parameters. The system then generates a revised summary incorporating the new segment and stylistic changes. This allows users to refine summaries without manual editing, ensuring the output aligns with evolving preferences while preserving the video's key elements. The approach enhances flexibility in automated video summarization, catering to diverse user needs without requiring full re-processing of the original video.
17. The system as recited in claim 16 , wherein the request to modify the first video summarization includes at least one of: an additional video segment from the video data but not included in the first video summarization to be added, the additional video segment corresponding to the second frame of the video data; at least one video segment included in the first video summarization be removed or replaced; or content depicted in the at least one video segment be modified.
This invention relates to a video summarization system that allows users to modify generated video summaries. The system creates a first video summarization from video data, where the summarization includes selected frames or segments from the original video. The system then receives a request to modify this summarization, which can include adding new video segments not originally included, removing or replacing existing segments, or altering the content within segments. The modifications are based on specific frames or segments from the original video data, ensuring consistency with the source material. This approach enables dynamic customization of video summaries to better meet user needs or preferences, addressing the challenge of static, inflexible summarization outputs. The system supports iterative refinement by allowing multiple adjustments to the summarization, improving usability for applications like content editing, surveillance, or media production. The invention ensures that modifications remain aligned with the original video data, maintaining accuracy and context.
18. The system as recited in claim 15 , wherein the operations further comprise: determining that a second frame of the video data depicts second content; determining that a third frame of the video data depicts third content; determining a second video segment that includes the second frame; determining a third video segment that includes the third frame; assigning a first rank to the second video segment based at least partly on the second content; assigning a second rank to the third video segment based at least partly on the third content; determining that the first rank is greater than the second rank; and selecting the second video segment to be included in the first video summarization.
Video analysis systems often struggle to automatically generate concise, high-quality summaries from lengthy video content. Existing methods may fail to accurately assess the importance of different video segments or may produce summaries that lack coherence or relevance. This invention addresses these challenges by providing a system that dynamically ranks and selects video segments based on their content to create an optimized video summarization. The system processes video data by analyzing individual frames to identify and categorize their content. For each frame, the system determines the corresponding video segment that includes that frame. Each segment is then assigned a rank based on the content it contains, with higher ranks indicating greater importance or relevance. The system compares the ranks of different segments and selects the highest-ranked segments for inclusion in the final video summarization. This ensures that the most significant portions of the video are prioritized, resulting in a summary that is both concise and informative. The ranking process can be tailored to specific criteria, such as user preferences or predefined relevance metrics, to further enhance the summarization's accuracy and usefulness.
19. The system as recited in claim 18 , wherein the operations further comprise determining that the one or more first summarization parameters include, in addition to the first directorial style, at least one of a preferred duration of the first video summarization, a preferred duration of video segments included within the first video summarization, or an acceptable level of entropy among at least the first video segment and the second video segment.
This invention relates to automated video summarization systems that generate concise video summaries based on user-defined parameters. The system addresses the challenge of creating personalized video summaries that balance brevity, coherence, and relevance by allowing users to specify summarization preferences. The system processes input video content and generates a summary by selecting key segments while adhering to user-defined constraints such as directorial style, duration, segment length, and acceptable entropy levels. Entropy measures the diversity or unpredictability of content, ensuring the summary maintains a desired level of variation or consistency. The system dynamically adjusts segment selection to meet these parameters, optimizing the summary for user preferences while preserving the most relevant content. This approach enhances user control over automated summarization, making it adaptable to different use cases, such as social media highlights, educational content, or professional presentations. The invention improves upon prior systems by incorporating multiple customizable parameters, allowing for more refined and personalized video summaries.
20. The system as recited in claim 15 , wherein the operations further comprise: assigning an interest value to the first frame based at least partly on the first content; determining that the interest value is above a threshold value; and selecting the first video segment to be included in the first video summarization.
This invention relates to video summarization systems that automatically generate concise video summaries by analyzing and selecting key segments from longer video content. The problem addressed is the need for efficient and automated methods to condense lengthy videos into shorter, more engaging summaries while preserving important content. The system processes a video by dividing it into multiple frames and segments. Each frame is analyzed to determine its content, such as objects, actions, or scenes. An interest value is assigned to each frame based on this content, reflecting its relevance or significance. If the interest value exceeds a predefined threshold, the corresponding video segment is selected for inclusion in the summary. This ensures that only the most engaging or important parts of the video are retained. The system may also compare frames or segments to identify redundancy, ensuring that similar content is not repeated in the summary. Additionally, the system may adjust the summarization process based on user preferences or contextual factors, such as the type of video (e.g., sports, news, or personal footage) or the intended use of the summary (e.g., social media sharing or quick review). The result is a dynamically generated video summary that balances brevity with content relevance.
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June 26, 2015
January 21, 2020
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